In designing exhaust silencers or mufflers for automobiles, the quality or timbre of the residual noise is often as important as the overall power level. The noise is characterized by a fundamental period which is related to the rotation rate of the engine, so the frequency spectrum has peaks at multiples of a fundamental frequency. This frequency changes as the speed of the engine changes. The frequency spectrum of the noise can be altered by the design of the passive silencer, but the quality of the noise is related to the relative levels of the various harmonics in the noise which cannot be controlled by a passive silencer.
Active noise cancellation techniques have been applied to automobile exhausts. These techniques seek to reduce the exhaust noise by adding noise with an equal amplitude but opposite phase. The system comprises an actuator, such as a loudspeaker or flow modulator, a sensor to monitor the residual noise and an electronic control system to determine the required drive signal for the actuator. The input to the control system can be a frequency or phase signal from a tachometer or the input can be from a sensor which is responsive to the sound pressure in the exhaust pipe or the input can be from the residual sensor itself (or it can be from a combination of these).
Active noise cancellation techniques seek to cancel as much of the offending noise as possible. The residual noise has an unpredictable quality and, although the total power is reduced, the residual noise may be subjectively worse than the original noise.
In the case of automotive mufflers or silencers, it is often not desirable to have a completely silent exhaust, since the quality of the exhaust noise will affect the character of the automobile.
There are many other applications where it is thought to be beneficial to adjust the frequency or harmonic content of a noise. These include noise inside aircraft and vehicle cabins. There is therefore a desire to be able to control the quality or shape of noise.
Control techniques have been used extensively in the areas of flight control and process control. One such technique is that of model reference control. In this approach the desired relationship between the input (command) signals and the system response is known in advance (this relationship is the `model`). An example of this type of system is shown in FIG. 1. The input signal, 1, is applied to both the physical system, 20, (via a regulator, 4) and to the model system, 21. The difference between the desired response, 6, and the actual physical response, 3, is used to generate an error signal, 22. The error signal and the input signal are used in adaption unit, 7, to adjust the regulator 4. (See Astrom and Wittenmark, `Adaptive Control`, Addison-Wesley Publishing Company, 1989, Section 1.2 for example, FIG. 1.2 in particular). These methods are designed to alter the effective response of the physical system, whereas the noise shaping control system of this invention is designed to alter the characteristics of a disturbance (there is no disturbance shown in FIG. 1, but this style of control system is usually designed to be insensitive to any disturbances).
The quality of a noise is best characterized by the shape of the frequency spectrum. There are several known techniques for canceling noise using frequency domain methods.
One approach is shown in FIG. 2. A reference input signal, 1, is input to a filter, 4, to produce the output signal, 2. An error signal, 3, related to the performance of the system is transformed in forward transform module, 6, to give the frequency spectrum of the error signal, 11. The input signal, 1, is transformed in forward transform module, 9, to give the frequency spectrum, 12. The frequency signals 11 and 12 are used in adaption unit 7 to estimate the transform of the filter response, 13. An inverse transform is applied in module 5 to provide a new filter characteristic.
An alternative approach is shown in FIG. 3. This configuration is the same except that the filtering is also performed in the frequency domain. The transform, 12, of the input signal is used together with the frequency domain filter, 4, to calculate the transform, 10, of the desired output signal. The inverse transform is then applied at 5 to produce the final output signal, 2.
A variation of this approach is shown in FIG. 4. This approach, which is designed for canceling periodic noise, is disclosed in U.S. Pat. No. 4,490,841 to Chaplin et al. The frequency transforms of 5 and 6 are synchronized to the frequency, 8, of a noise source. This means that the output of transform module 6 provides the complex amplitudes of the harmonic components of the residual signal, 3. This approach has been applied successfully to muffler noise cancellation where the frequency signal is provided by a tachometer signal.
The system is equivalent to using an input signal with a unity harmonic spectrum. The reference input, 1, is shown for comparison to the other schemes. It is not a physical input.
This technique provides a means for canceling selected harmonics of the noise, but there is no mechanism for determining or controlling the degree of cancellation.
One of the common adaption algorithms used in the adaption module is the filtered-input (filtered-x) LMS algorithm (Widrow and Steams, `Adaptive Signal Processing`, Prentice Hall, 1985, p288-294). One feature of this algorithm is that the adaption rate is dependent on the level and frequency content of the input signal. In the approach disclosed by Sjosten et al, (Proceedings of Inter-noise 90, Gothenburg, Sweden, 1990, pp1251-1254) the input signal is a sum of sinusoids synchronized to the frequency of the engine. By adjusting the relative levels of these input signals the relative rate of adaption of the harmonics can be varied. This approach has limited use since the adaption rate alone does not determine the levels of residual noise.
In other approaches the harmonics are controlled separately, so a different adaption step size can be used for each harmonic to control the relative rate of adaption.
However, neither of these approaches directly govern the amount of cancellation of the harmonics. For example, for a steady signal they will still attempt to cancel all of the noise and for transient signals the reduction will depend on the rate of change of the noise.
Another approach for altering the levels of the residual noise requires that the desired residual signals are known in advance. This method can be used for periodic or broadband noise. The desired signal can be subtracted from the residual signal before being used in the adaption algorithm. However, it is not practical to supply a desired signal for the whole range of operating conditions.